In many communication systems, tones composed of multiple sinusoidal components are used for signalling. For example, Dual Tone Multiple Frequency (DTMF) signalling is a technique using a set of signalling tones with each tone being composed of two frequency components. In telephone systems, DTMF can be used for tone dialing. A key pressed on a telephone set generates a dual-frequency tone composed of a low frequency and a high frequency component. Other examples of signalling techniques having signalling tones being composed of multiple sinusoidal components are, for example, Multiple Frequency MF-R1 and MF-R2. Another example is a telephone off-hook warning tone that may be generated using multiple (e.g. four) frequency components.
Tone detectors are frequently used in communication systems for monitoring received signals and identifying a presence of pre-defined signalling tones. There are many practical situations, however, when signalling tones are highly corrupted by noise, which may end up disrupting expected tone detection functionality. Tone detection methods often handle noisy situations by post-processing with low-pass filters. However, due to frequency and timing tolerance requirements, false detection rates tend to increase as noise distortion increases beyond critical levels. A correct detection and identification of a tone received on a transmission channel, e.g. a telephone line, is achieved by accurately estimating frequencies contained in the tone, considering transmission aspects, for example noise, network distortions, and distinction between signalling tones and tone-like speech etc.
An approach for multi-component tone detection can be based on transforming the received signal into a frequency domain, for example using standard Fourier Transform methods. However, some of these methods are generally not applicable to more than two components, some allow handling of DTMF signalling only, are of very high complexity or require too much time for tone detection.
Other approaches are available, detecting multi-component tones based on the evaluation of polynomial filters results, for example energy operators as described in the document “Detection of multi-tone signals based on energy operators”, 1994 IEEE 0-7803-2127-8/94 by E. F. Velez. It describes a nonlinear approach based on the Teager-Kaiser energy operator for multi-tone detection in the presence of voice. The shown approach is limited to detecting signals with two frequency components.
The document US 2004/0047370 A1 discloses a method for multicomponent tone detection based on Teager-Kaiser energy operators as described by Velez.
The document US 2005/0195967 A1 describes a tone event detector, which first determines whether the presence of a tone is indicated on the input signal, and then, based on this determination, selectively determines whether a tone has been detected on the input signal.
The document US 2007/0263842 A1 discloses an enhanced tone detector including an adaptive multi-bandpass filter improving tone detection and enhancing performance during noisy signalling conditions.